How does Coderadius differ from observability tools?
Coderadius builds its graph statically from code, not from runtime traffic, so it works before deployment.
@coderadius-ai
基本信息
Prevent cross-repo architectural breakage before merge. Architecture knowledge graph from static analysis, blast radius in CI, MCP server for AI agents.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"coderadius": {
"args": [
"mcp",
"start"
],
"command": "cr"
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
Coderadius is a static analysis tool that builds a live knowledge graph of your entire architecture across every service, API, queue, and database. It helps engineers and AI agents measure blast radius, enforce policy, and prevent cross-repo breaking changes before merge.
Install via npm i -g coderadius or the install script, then run cr init to configure, cr up to start the local graph database, cr analyze code . to build the graph, cr blast to check impact of current changes, and cr mcp start to start the MCP server for AI agents.
Coderadius builds its graph statically from code, not from runtime traffic, so it works before deployment.
Docker for the local graph database and a self-contained binary for macOS or Linux. No other dependencies.
No. Coderadius is local-first; your code never leaves your machine. You can use a local LLM via Ollama or bring your own API key.
Language support includes TypeScript, PHP, Python, Go, and Java. Several frameworks are eval-verified, others are heuristic+LLM.
Coderadius is 0.x and moving fast. The deterministic core is well-tested, but LLM extraction quality varies and the CLI surface may change without migration paths.
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